Closed-loop geothermal systems (CLGSs) rely on circulation of a heat transfer fluid in a closed-loop design without penetrating the reservoir to extract subsurface heat and bring it to the surface. We developed and applied numerical models to study u-shaped and coaxial CLGSs in hot-dry-rock over a more comprehensive parameter space than has been studied before, including water and supercritical CO2 (sCO2) as working fluids. An economic analysis of each realization was performed to evaluate the levelized cost of heat (LCOH) for direct heating application and levelized cost of electricity (LCOE) for electrical power generation. The results of the parameter study, composed of 2.5 million simulations, combined with a plant and economic model comprise the backbone of a publicly accessible web application that can be used to query, analyze, and plot outlet states, thermal and mechanical power output, and LCOH/LCOE, thereby facilitating feasibility studies led by potential developers, geothermal scientists, or the general public (https://gdr.openei.org/submissions/1473). Our results indicate competitive LCOH can be achieved; however, competitive LCOE cannot be achieved without significant reductions in drilling costs. We also present a site-based case study for multi-lateral systems and discuss how our comprehensive single-lateral analyses can be applied to approximate multi-lateral CLGSs. Looking beyond hot-dry-rock, we detail CLGS studies in permeable wet rock, albeit for a more limited parameter space, indicating that reservoir permeability of greater than 250 mD is necessary to significantly improve CLGS power production, and that reservoir temperatures greater than 200 °C, achieved by going to greater depths (∼3–4 km), may significantly enhance power production.
Accurate modeling of subsurface flow and transport processes is vital as the prevalence of subsurface activities such as carbon sequestration, geothermal recovery, and nuclear waste disposal increases. Computational modeling of these problems leverages poroelasticity theory, which describes coupled fluid flow and mechanical deformation. Although fully coupled monolithic schemes are accurate for coupled problems, they can demand significant computational resources for large problems. In this work, a fixed stress scheme is implemented into the Sandia Sierra Multiphysics toolkit. Two implementation methods, along with the fully coupled method, are verified with one-dimensional (1D) Terzaghi, 2D Mandel, and 3D Cryer sphere benchmark problems. The impact of a range of material parameters and convergence tolerances on numerical accuracy and efficiency was evaluated. Overall the fixed stress schemes achieved acceptable numerical accuracy and efficiency compared to the fully coupled scheme. However, the accuracy of the fixed stress scheme tends to decrease with low permeable cases, requiring the finer tolerance to achieve a desired numerical accuracy. For the fully coupled scheme, high numerical accuracy was observed in most of cases except a low permeability case where an order of magnitude finer tolerance was required for accurate results. Finally, a two-layer Terzaghi problem and an injection–production well system were used to demonstrate the applicability of findings from the benchmark problems for more realistic conditions over a range of permeability. Simulation results suggest that the fixed stress scheme provides accurate solutions for all cases considered with the proper adjustment of the tolerance. This work clearly demonstrates the robustness of the fixed stress scheme for coupled poroelastic problems, while a cautious selection of numerical tolerance may be required under certain conditions with low permeable materials.
Prediction of flow, transport, and deformation in fractured and porous media is critical to improving our scientific understanding of coupled thermal-hydrological-mechanical processes related to subsurface energy storage and recovery, nonproliferation, and nuclear waste storage. Especially, earth rock response to changes in pressure and stress has remained a critically challenging task. In this work, we advance computational capabilities for coupled processes in fractured and porous media using Sandia Sierra Multiphysics software through verification and validation problems such as poro-elasticity, elasto-plasticity and thermo-poroelasticity. We apply Sierra software for geologic carbon storage, fluid injection/extraction, and enhanced geothermal systems. We also significantly improve machine learning approaches through latent space and self-supervised learning. Additionally, we develop new experimental technique for evaluating dynamics of compacted soils at an intermediate scale. Overall, this project will enable us to systematically measure and control the earth system response to changes in stress and pressure due to subsurface energy activities.
Greater utilization of subsurface reservoirs perturbs in-situ chemical-mechanical conditions with wide ranging consequences from decreased performance to project failure. Understanding the chemical precursors to rock deformation is critical to reducing the risks of these activities. To address this need, we investigated the coupled flow-dissolution- precipitation-adsorption reactions involving calcite and environmentally-relevant solid phases. Experimentally, we quantified (1) stable isotope fractionation processes for strontium during calcite nucleation and growth, and during reactive fluid flow; (2) consolidation behavior of calcite assemblages in the common brines. Numerically, we quantified water weakening of calcite using molecular dynamics simulations; and quantified the impact of calcite dissolution rate on macroscopic fracturing using finite element models. With microfluidic experiments and modeling, we show the effect of local flow fields on the dissolution kinetics of calcite. Taken together across a wide range of scales and methods, our studies allow us to separate the effects of reaction, flow, and transport, on calcite fracturing and the evolution of strontium isotopic signatures in the reactive fluids.
Recent advances in drilling technology, especially horizontal drilling, have prompted a renewed interest in the use of closed loop geothermal energy extraction systems. Deeply placed closed loops in hot wet or dry rock reservoirs offer the potential to exploit the vast thermal energy in the subsurface. To better understand the potential and limitations for recovering thermal and mechanical energy from closed-loop geothermal systems (CLGS), a collaborative study is underway to investigate an array of system configurations, working fluids, geothermal reservoir characteristics, operational periods, and heat transfer enhancements (Parisi et al., 2021; White et al., 2021). This paper presents numerical results for the heat exchange between a closed loop system (single U-tube) circulating water as the working fluid in a hot rock reservoir. The characteristics of the reservoir are based on the Frontier Observatory for Research in Geothermal Energy (FORGE) site, near Milford Utah. To determine optimal system configurations, a mechanical (electrical) objective function is defined for a bounded optimization study over a specified design space. The objective function includes a surface plant thermal to mechanical energy conversion factor, pump work, and an energy drilling capital cost. To complement the optimization results, detailed parametric studies are also performed. The numerical model is built using the Sandia National Laboratories (SNL) massively parallel Sierra computational framework, while the optimization and parametric studies are driven using the SNL Dakota software package. Together, the optimization and parametric studies presented in this paper will help assess the impact of CLGS parameters (e.g., flow rate, tubing length and diameter, insulation length, etc.) on CLGS performance and optimal energy recovery.
Predicting performance of parts produced using laser-metal processing remains an out- standing challenge. While many computational models exist, they are generally too computationally expensive to simulate the build of an engineering-scale part. This work develops a reduced order thermal model of a laser-metal system using analytical Green's function solutions to the linear heat equation, representing a step towards achieving a full part performance prediction in an "overnight" time frame. The developed model is able to calculate a thermal history for an example problem 72 times faster than a traditional FEM method. The model parameters are calibrated using a non-linear solution and microstructures and residual stresses calculated and compared to a non-linear case. The calibrated model shows promising agreement with a non-linear solution.
Coupled fluid-flow and geomechanical analysis of caprock integrity has gained a lot of attention among scientists and researchers investigating the long-term performance of geologic carbon storage systems. Reactivation of pre-existing fractures within the caprock or re-opening of faults can create permeable pathways which can influence the seal integrity. Stability of the caprock during and after injection of super-critical CO2, and the impact of pre-existing fractures in the presence or absence of one or multiple faults have been investigated in this study. The impact of the wellbore orientation and the injection rate are among other key factors in understanding the structural trapping mechanisms within such geological formations. In this study, we numerically investigated the impact of each of these factors. This study revealed the interplay between joints and faults and how different leakage pathways are formed and under which scenario they play a dominant role in terms of CO2 leakage. Finally, this study also highlights the role of one versus multiple faults in the domain and the importance of the fault hydrological property in forming leakage pathway.
The National Solar Thermal Test Facility (NSTTF) at Sandia National Laboratories is conducting research on a Generation 3 Particle Pilot Plant (G3P3) that uses falling sand-like particles as the heat transfer medium. The system will include a thermal energy storage (TES) bin with a capacity of 6 MWht¬ requiring ~120,000 kg of flowing particles. Testing and modeling were conducted to develop a validated modeling tool to understand temporal and spatial temperature distributions within the storage bin as it charges and discharges. Flow and energy transport in funnel-flow was modeled using volume averaged conservation equations coupled with level set interface tracking equations that prescribe the dynamic geometry of particle flow within the storage bin. A thin layer of particles on top of the particle bed was allowed to flow toward the center and into the flow channel above the outlet. Model results were validated using particle discharge temperatures taken from thermocouples mounted throughout a small steel bin. The model was then used to predict heat loss during charging, storing, and discharging operational modes at the G3P3 scale. Comparative results from the modeling and testing of the small bin indicate that the model captures many of the salient features of the transient particle outlet temperature over time.
The National Solar Thermal Test Facility (NSTTF) at Sandia National Laboratories is conducting research on a Generation 3 Particle Pilot Plant (G3P3) that uses falling sand-like particles as the heat transfer medium. The system will include a thermal energy storage (TES) bin with a capacity of 6 MWht¬ requiring ~120,000 kg of flowing particles. Testing and modeling were conducted to develop a validated modeling tool to understand temporal and spatial temperature distributions within the storage bin as it charges and discharges. Flow and energy transport in funnel-flow was modeled using volume averaged conservation equations coupled with level set interface tracking equations that prescribe the dynamic geometry of particle flow within the storage bin. A thin layer of particles on top of the particle bed was allowed to flow toward the center and into the flow channel above the outlet. Model results were validated using particle discharge temperatures taken from thermocouples mounted throughout a small steel bin. The model was then used to predict heat loss during charging, storing, and discharging operational modes at the G3P3 scale. Comparative results from the modeling and testing of the small bin indicate that the model captures many of the salient features of the transient particle outlet temperature over time.
In this work, we have characterized the calcium carbonate (CaCO3) precipitates over time caused by reaction-driven precipitation and dissolution in a micromodel. Reactive solutions were continuously injected through two separate inlets, resulting in transverse-mixing induced precipitation during the precipitation phase. Subsequently, a dissolution phase was conducted by injecting clean water (pH = 4). The evolution of precipitates was imaged in two and three dimensions (2-, 3-D) at selected times using optical and confocal microscopy. With estimated reactive surface area, effective precipitation and dissolution rates can be quantitatively compared to results in the previous works. Our comparison indicates that we can evaluate the spatial and temporal variations of effective reactive areas more mechanistically in the microfluidic system only with the knowledge of local hydrodynamics, polymorphs, and comprehensive image analysis. Our analysis clearly highlights the feedback mechanisms between reactions and hydrodynamics. Pore-scale modeling results during the dissolution phase were used to account for experimental observations of dissolved CaCO3 plumes with dissolution of the unstable phase of CaCO3. Mineral precipitation and dissolution induce complex dynamic pore structures, thereby impacting pore-scale fluid dynamics. Pore-scale analysis of the evolution of precipitates can reveal the significance of chemical and pore structural controls on reaction and fluid migration.
This SAND report fulfills the final report requirement for the Born Qualified Grand Challenge LDRD. Born Qualified was funded from FY16-FY18 with a total budget of ~$13M over the 3 years of funding. Overall 70+ staff, Post Docs, and students supported this project over its lifetime. The driver for Born Qualified was using Additive Manufacturing (AM) to change the qualification paradigm for low volume, high value, high consequence, complex parts that are common in high-risk industries such as ND, defense, energy, aerospace, and medical. AM offers the opportunity to transform design, manufacturing, and qualification with its unique capabilities. AM is a disruptive technology, allowing the capability to simultaneously create part and material while tightly controlling and monitoring the manufacturing process at the voxel level, with the inherent flexibility and agility in printing layer-by-layer. AM enables the possibility of measuring critical material and part parameters during manufacturing, thus changing the way we collect data, assess performance, and accept or qualify parts. It provides an opportunity to shift from the current iterative design-build-test qualification paradigm using traditional manufacturing processes to design-by-predictivity where requirements are addressed concurrently and rapidly. The new qualification paradigm driven by AM provides the opportunity to predict performance probabilistically, to optimally control the manufacturing process, and to implement accelerated cycles of learning. Exploiting these capabilities to realize a new uncertainty quantification-driven qualification that is rapid, flexible, and practical is the focus of this effort.
Injection of large amounts of fluid into the subsurface alters the states of pore pressure and stress in the formation, potentially inducing earthquakes. Increase in the seismicity rate after shut-in is often observed at fluid-injection operation sites, but mechanistic study of the rate surge has not been investigated thoroughly. Considering full poroelastic coupling of pore pressure and stress, the earthquake occurrence after shut-in can be driven by two mechanisms: (1) post shut-in diffusion of pore pressure into distant faults and (2) poroelastic stressing caused by fluid injection. Interactions of these mechanisms can depend on fault geometry, hydraulic and mechanical properties of the formation, and injection operation. In this work, a 2D aerial view of the target reservoir intersected by strike-slip basement faults is used to evaluate the impact of injection-induced pressure buildup on seismicity rate surge. A series of sensitivity tests are performed by considering the variation in (1) permeability of the fault zone, (2) locations and the number of faults with respect to the injector, and (3) well operations with time-dependent injection rates. Lower permeability faults have higher seismicity rates than more permeable faults after shut-in due to delayed diffusion and poroelastic stressing. Hydraulic barriers, depending on their relative location to injection, can either stabilize or weaken a conductive fault via poroelastic stresses. Gradual reduction of the injection rate minimizes the coulomb stress change and the least seismicity rates are predicted due to slower relaxation of coupling-induced compression as well as pore-pressure dissipation.
The fluid injection into deep geological formations altar the states of pore pressure and stress on the faults, potentially causing earthquakes. In the multiphase flow system, the interaction between fluid flow and mechanical deformation in porous media is critical to determine the spatio-temporal distribution of pore pressure and stress. The contrast of fluid and rock properties between different structures produces the changes in pressure gradients and subsequently stress fields. Assuming two-phase fluid flow (gas-water system), we simulate the two-dimensional reservoir including a basement fault, in which injection-induced pressure encounters the fault directly given injection scenarios. The single-phase flow model with the same setting is also conducted to evaluate the multiphase flow effects on mechanical response of the fault to gas injection. A series of sensitivity tests are performed by varying the fault permeability. The presence of gaseous phase reduces the pressure buildup within the gas-saturated region, causing less Coulomb stress change. The low-permeability fault prevent diffusion initially as observed in the single-phase flow system. Once gaseous phase approaches, the fault acts as a capillary barrier that causes increases in pressure within the fault zone, potentially inducing earthquakes even without direct diffusion.